毕业设计（论文）--基于Matlab的数字图像边缘检测算法研究_精品.docVIP

毕业设计（论文）--基于Matlab的数字图像边缘检测算法研究 Abstract In image processing, as a basic characteristic, the edge of the image, which is widely used in the recognition, segmentation, intensification and compress of the image, is often applied to high-level domain. Edge detection is one of the most fundamentals in image processing and analyzing, which is still unsolved. Image’s edges include image’s features such as position and outline, which belong to the fundamental features. Edge detection is widely used in image analysis and processing such as feature description, image segmentation, image enhancement, pattern recognition and image compression etc, so Edge Detection and extract of outline figure are the research hotspot in the technology of image processing and analysis all, on which the new theory and methods are put forward constantly. Some edge detection algorithms are researched, including Roberts, Sobel, Prewitt, LoG, Canny, Kirsch etc. The classic edge detection methods have some drawbacks in image denoising. The main idea of resolving this problem is to set a threshold, then compare the threshold with the high-frequency components of an image to remove the noise.The choice of the threshold is the key of image denoising. The threshold of traditional methods is obtained by experiments, and there is no general method to determine it. A new method of edge estimation by the imum a Posteriori MAP is presented in this paper. It proves how to choose the optimal threshold in theory. These algorithms are introduced in detail, and the steps of algorithm realization are introduce too.The algorithm is tested by simulation. The main aim of the paper is studying Performance Evaluation in edge detection algorithms, and the detection results are compared. The experiments results show that the algorithms can be a useful reference of latter parts of image processing. Keywords: edge detection; image processing; Matlab; Sobel; detection algorithm 引 言 图像边缘是图像最基本的特征之一，往往携带着一幅图像的大部分信息。而边